{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T21:45:14Z","timestamp":1769550314447,"version":"3.49.0"},"reference-count":34,"publisher":"SPE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Stuck pipe is a common worldwide drilling problem, resulting significant increases in non-productive time and overall well cost. Many oil and gas reservoirs are mature and are becoming increasingly depleted of hydrocarbons which make stuck pipe more severe risks. This is due to the fact that decreasing pore pressure increases the chance of stuck pipe. Minimizing the risks of stuck pipe while drilling has been the goal of many operators recently. This paper describes a robust support vector regression (SVR) methodology that offers superior performance for stuck pipe prediction either mechanically or differentially using available drilling parameters. A new model is developed using drilling parameters such as measured depth, mud weight, plastic viscosity, yield point, gel strengths, PH and solid percent from different wells. The method incorporates hybrid least square support vector regression and Coupled Simulated Annealing (CSA) optimization technique (LSSVM-CSA) for efficient tuning of SVR hyper parameters. The algorithm is applied to classify the stuck types, i.e., differential stuck or mechanical stuck. Performance analysis shows that LSSVM classifier has high accuracy. Using intelligent system would help drilling industry to reduce Non-Productive Time (NPT) during operation in complex zones.<\/jats:p>","DOI":"10.2118\/164003-ms","type":"proceedings-article","created":{"date-parts":[[2013,1,28]],"date-time":"2013-01-28T08:02:11Z","timestamp":1359360131000},"source":"Crossref","is-referenced-by-count":31,"title":["Support Vector Machine Model: A New Methodology for Stuck Pipe Prediction"],"prefix":"10.2118","author":[{"given":"Ali","family":"Chamkalani","sequence":"additional","affiliation":[{"name":"Petroleum University of Technology, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mojtaba","family":"Pordel Shahri","sequence":"additional","affiliation":[{"name":"Petroleum University of Technology, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saeed","family":"Poordad","sequence":"additional","affiliation":[{"name":"Petroleum University of Technology, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"861","published-online":{"date-parts":[[2013,1,28]]},"reference":[{"key":"2025031718253232400_R1","volume-title":"Simulated Annealing and Boltzmann Machines","author":"Aarts","year":"1989"},{"key":"2025031718253232400_R2","volume-title":"Support Vector Machines for Pattern Classification","author":"Abe","year":"2005"},{"key":"2025031718253232400_R3","doi-asserted-by":"crossref","unstructured":"Belaskie, J.P., McCann, D.P. and Leshikar, J.F.\n          1994. A Practical Method To Minimize Stuck Pipe Integrating Surface and MWD Measurements. Paper SPE 27494 presented at the IADC\/SPE Drilling Conference, Dallas, Texas, 15-18 February.","DOI":"10.2523\/27494-MS"},{"key":"2025031718253232400_R4","doi-asserted-by":"crossref","unstructured":"Biegler, M.W. and Kuhn, G.R.\n          1994. Advances in Prediction of Stuck Pipe Using Multivariate Statistical Analysis. Paper SPE 27529 presented at the SPE\/IADC Drilling Conference, Dallas, Texas, 15-18 February.","DOI":"10.2523\/27529-MS"},{"issue":"3","key":"2025031718253232400_R10","doi-asserted-by":"crossref","first-page":"237","DOI":"10.2118\/14181-PA","article-title":"Multivariate Statistical Analysis of Stuck Drillpipe Situations","volume":"2","author":"Hempkins","year":"1987","journal-title":"SPE Drill Eng"},{"key":"2025031718253232400_R11","doi-asserted-by":"crossref","unstructured":"Hopkins, C.J. and Leicksenring, R.A.\n          1995. Reducing the risk of stuck pipe in the Netherlands. Paper SPE 29422 presented at the SPE\/IADC Drilling Conference, Amsterdam, Netherlands, 28 February-2 March.","DOI":"10.2523\/29422-MS"},{"key":"2025031718253232400_R12","doi-asserted-by":"crossref","unstructured":"Howard, J.A. and Glover, S.B.\n          1994. Tracking Stuck Pipe Probability While Drilling. Paper SPE 27528 presented at the SPE\/IADC Drilling Conference, Dallas, Texas, 15-18 February.","DOI":"10.2118\/27528-MS"},{"issue":"2","key":"2025031718253232400_R5","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1009715923555","article-title":"Tutorial on Support Vector Machines For Pattern Recognition","volume":"2","author":"Burges","year":"1998","journal-title":"Data Min Knowl Discov"},{"key":"2025031718253232400_R6","article-title":"A Novel Technique for Screening of Asphaltene Deposition by Pattern Recognition Method","author":"Chamkalani","year":"2011","journal-title":"Energy Sources, Part A: Recovery, Utilization, and Environmental Effects"},{"key":"2025031718253232400_R7","doi-asserted-by":"crossref","unstructured":"Charlez, P.A. and Onaisi, A.\n          1998. Three Histofy Cases of Rock Mechanics related Stuck Pipes while drilling Extended Reach wells in North Sea. Paper SPE 47287 presented at the SPE\/ISRM Rock Mechanics in Petroleum Engineering, Trondheim, Norway, 8-10 July.","DOI":"10.2118\/47287-MS"},{"key":"2025031718253232400_R8","doi-asserted-by":"crossref","unstructured":"Courteille, J.M. and Zurdo, C.\n          1985. A New Approach to Differential Sticking. Paper SPE 14244 presented at the SPE Annual Technical Conference and Exhibition, Las Vegas, Nevada,\u00a0, 22-26 September.","DOI":"10.2118\/14244-MS"},{"key":"2025031718253232400_R9","doi-asserted-by":"crossref","unstructured":"Gulsrud, T. O., NybO, R. and BjOrkevoll, K.S.\n          2009. Statistical Method for Detection of Poor Hole Cleaning and Stuck Pipe. Paper SPE 123374 presented at the Offshore Europe, Aberdeen, UK, 8-11 September.","DOI":"10.2118\/123374-MS"},{"key":"2025031718253232400_R13","doi-asserted-by":"crossref","unstructured":"Isambourg, P., Ottesen, S., Benaissa, S. and Marti, J.\n          1999. Down-Hole Simulation Cell for Measurement of Lubricity and Differential Pressure. Paper SPE 52816 presented at the SPE\/IADC Drilling Conference, Amsterdam, Netherlands, 9-11 March.","DOI":"10.2118\/52816-MS"},{"issue":"4598","key":"2025031718253232400_R14","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","author":"Kirkpatrick","year":"1983","journal-title":"Science"},{"issue":"2\u20133","key":"2025031718253232400_R15","article-title":"Glossary of terms","volume":"30","author":"Kohavi","year":"1998","journal-title":"Editorial for the Special Issue on Applications of Machine Learning and the Knowledge Discovery Process"},{"key":"2025031718253232400_R16","doi-asserted-by":"crossref","unstructured":"Meschi, M. R., Shahbazi, K. and Pordel Shahri, M.\n          2010. A New Criteria to Predict Stuck Pipe Occurrence. Paper SPE 128376 presented at the North Africa Technical Conference and Exhibition, Cairo, Egypt, 14-17 February.","DOI":"10.2523\/128376-MS"},{"key":"2025031718253232400_R17","doi-asserted-by":"crossref","unstructured":"Miri, R., Sampaio, J., Afshar, M. and Lourenco, A.\n          2007. Development of Artificial Neural Networks to Predict Differential Pipe Sticking in Iranian Offshore Oil Fields. Paper SPE 108500 presented at the International Oil Conference and Exhibition in Mexico, Veracruz, Mexico, 27-30 June.","DOI":"10.2118\/108500-MS"},{"issue":"6","key":"2025031718253232400_R18","first-page":"5570","article-title":"Stuck Drill Pipe Prediction with Networks Neural in Maroon Field","volume":"2","author":"MoradiNezhad","year":"2012","journal-title":"J Basic Appl Sci Res"},{"key":"2025031718253232400_R19","doi-asserted-by":"crossref","unstructured":"Murillo, A., Neuman, J. and Samuel, R.\n          2009. Pipe Sticking Prediction and Avoidance Using Adaptive Fuzzy Logic Modeling. Paper SPE 120128 presented at the SPE Production and Operations Symposium, Oklahoma City, Oklahoma, 4-8 April.","DOI":"10.2118\/120128-MS"},{"key":"2025031718253232400_R20","first-page":"586","article-title":"Artificial neural networks for diagnosis of hepatitis disease","volume":"1","author":"Ozyilmaz","year":"2003","journal-title":"Proceedings of the International Joint Conference on Neural Networks"},{"issue":"4","key":"2025031718253232400_R21","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1016\/j.dsp.2006.10.008","article-title":"Breast cancer diagnosis using least square support vector machine","volume":"17","author":"Polat","year":"2007","journal-title":"Digital Signal Processing"},{"key":"2025031718253232400_R22","doi-asserted-by":"crossref","unstructured":"Reid, P.I., Meeten, G.H., Way, P.W., Clark, P., Chambers, B.D., Gilmour, A. and Sanders, M.W.\n          1996. Differential \u2013Sticking Mechanisms and a Simple Wellsite Test for Monitoring and optimizing Drilling Mud Properties. Paper SPE 35100 presented at the SPE\/IADC Drilling Conference, New Orleans, Louisiana, 12-15 March.","DOI":"10.2523\/35100-MS"},{"issue":"4","key":"2025031718253232400_R23","article-title":"Drilling Stuck Pipe Prediction in Iranian Oil Fields: An Artificial Neural Network Approach","volume":"7","author":"Shadizadeh","year":"2010","journal-title":"IAChE"},{"key":"2025031718253232400_R24","doi-asserted-by":"crossref","unstructured":"Shadravan, A., Khodadadian, M., Roohi, A.\n          2009. Underbalanced Drilling in Depleted Formation Achieves Great Success: Case Study. Paper SPE 119211 presented at EUROPEC\/EAGE Conference and Exhibition, Amsterdam, The Netherlands, 8-11 June.","DOI":"10.2118\/119211-MS"},{"key":"2025031718253232400_R25","doi-asserted-by":"crossref","unstructured":"Shadravan, A., Nabaei, M., and Amani, M.\n          2009. Dealing with the Challenges of UBD Implementation in Southern Iranian Oilfields. Paper SPE 125281 presented at SPE\/IADC Middle East Drilling Technology Conference & Exhibition, Manama, Bahrain, 26-28 October.","DOI":"10.2118\/125281-MS"},{"key":"2025031718253232400_R26","doi-asserted-by":"crossref","unstructured":"Shadravan, A., Nabaei, M., and Amani, M.\n          2009. Utilizing UBD Technology for Future Development of Parsi Oilfield, Challenges and Opportunities. Paper SPE 123270 presented at Offshore Europe, Aberdeen, UK, 8-11 September.","DOI":"10.2118\/123270-MS"},{"issue":"2","key":"2025031718253232400_R27","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1080\/10916461003792302","article-title":"The Development of a Window for Stuck Pipe Prediction","volume":"30","author":"Shahbazi","year":"2012","journal-title":"Petroleum Science and Technology"},{"issue":"2","key":"2025031718253232400_R28","doi-asserted-by":"crossref","first-page":"125","DOI":"10.2118\/21998-PA","article-title":"Operational decision making for stuck pipe incidents in the Gulf of Mexico: A risk economics approach","volume":"8","author":"Shivers","year":"1993","journal-title":"SPE Drill & Compl"},{"key":"2025031718253232400_R29","doi-asserted-by":"crossref","unstructured":"Shoraka, S.A. R, Shadizadeh, S.R. and PordelShahri, M.\n          2011. Prediction of Stuck Pipe in Iranian South Oil Fields Using Multivariate Statistical Analysis. Paper SPE 151076 presented at the Nigeria Annual International Conference and Exhibition, Abuja, Nigeria, 30 July \u2013 3 August.","DOI":"10.2118\/151076-MS"},{"key":"2025031718253232400_R30","doi-asserted-by":"crossref","unstructured":"Siruvuri, C., Nagarakanti, S. and Samuel, R.\n          2006. Stuck Pipe Prediction and Avoidance: A Convolutional Neural Network Approach. Paper SPE 98378 presented at the IADC\/SPE Drilling Conference, Miami, Florida, 21-23 February.","DOI":"10.2118\/98378-MS"},{"issue":"3","key":"2025031718253232400_R31","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","article-title":"Least squares support vector machine classifiers","volume":"9","author":"Suykens","year":"1999","journal-title":"Neural Process Lett"},{"key":"2025031718253232400_R32","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The Nature Of Statistical Learning Theory","author":"Vapnik","year":"1995","edition":"2nd ed."},{"key":"2025031718253232400_R33","unstructured":"Warren, J. E.\n          \n          1940. Causes, Preventions, and Recovery of Stuck Drill Pipe. Paper API 40-030 presented at the Drilling and Production Practice."},{"issue":"2","key":"2025031718253232400_R34","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1109\/TSMCB.2009.2020435","article-title":"Coupled Simulated Annealing","volume":"40","author":"Xavier-de-Souza","year":"2010","journal-title":"IEEE Transactions on Systems, Man and Cybernetics, Part B"}],"event":{"name":"SPE Unconventional Gas Conference and Exhibition","location":"Muscat, Oman","acronym":"13UGM","start":{"date-parts":[[2013,1,28]]},"end":{"date-parts":[[2013,1,30]]}},"container-title":["SPE Unconventional Gas Conference and Exhibition"],"original-title":[],"link":[{"URL":"https:\/\/onepetro.org\/SPEUGM\/proceedings-pdf\/doi\/10.2118\/164003-MS\/1583309\/spe-164003-ms.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/onepetro.org\/SPEUGM\/proceedings-pdf\/doi\/10.2118\/164003-MS\/1583309\/spe-164003-ms.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T18:25:44Z","timestamp":1742235944000},"score":1,"resource":{"primary":{"URL":"https:\/\/onepetro.org\/SPEUGM\/proceedings\/13UGM\/13UGM\/SPE-164003-MS\/178844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,28]]},"references-count":34,"URL":"https:\/\/doi.org\/10.2118\/164003-ms","relation":{},"subject":[],"published":{"date-parts":[[2013,1,28]]},"article-number":"SPE-164003-MS"}}